How ML Works in Paraphrase Tool for New Content?

Artificial Intelligence is rapidly making its way to every field of life and writing is no exception. Whether you use a plagiarism checker, paraphrase tool, summary generator, or grammar checker, most of them are working on the sub-branches of AI – Machine Learning and Natural Language Processing. But the backend mechanism of such tools is not as simple as it sounds.

Thus, this guide is for you if you want to understand how ML works in paraphrasing and other tools. And without wasting any time, let’s begin.

What Is Machine Learning?

Machine learning (ML) is one of the most popular branches of Artificial Intelligence that learns from the generated data and experience to automate users’ tasks. So, it doesn’t rely on elements like user inputs.

The text prediction of a smartphone’s keyboard according to the typing style of users is the best example of machine learning. Similarly, the grammar checkers or most paraphrasing tools you use daily are other prime examples of machine learning. So, machine learning works in the following steps:

• First, it collects the data and material.
• Then, it prepares and chooses the model.
• The third step is to train the model according to the collected data or material and evaluate the training procedure for the system’s accuracy.
• The last step is the prediction and forecasting phase.

So, according to the above-discussed steps, let’s see the working of paraphrasing tool and the role of machine learning and other branches of AI in its working.

How Does Machine Learning Work in Paraphrase Tools?

You can only understand the role of Machine Learning in paraphrasing tools by analyzing their working mechanism. So, let’s see how ML works in AI paraphrase tool for new content generation through the three phases of AI-based paraphrasing tools.

1.  Making the Content Easier to Understand for Machine:

Machines do not communicate in the language of humans. So, to make them understand your input, you will have to convert it to machine language. That’s what the first phase of AI paraphrasing tools does.

The developers of the best paraphrasing tools use Natural Language Processing (NLP) to convert the input into machine-friendly language. NLP is a branch of Artificial Intelligence that enables machines to understand the text and spoken words like humans. So, paraphrasing tools use the NLP algorithm to understand the input by converting it to machine language.

This phase is the backbone of most modern paraphrasing and summarizing tools because those tools catch the theme and meanings of specific words here.

2.  Detecting the Content Itself:

When developers have used the correct machine learning aspects in developing paraphrasing tools, paraphrasing tools can easily and quickly understand the intent of the content. So, the second phase is detecting the content itself.

Besides NLP, machine learning plays a vital role in this phase. ML and NLP help the paraphrasing tools understand the intent of information. So, when they go to the actual paraphrasing phase, they can keep the meaning of source content intact.

Understanding the intent of the content is also essential while checking the originality of the content. So, some modern AI-based plagiarism checkers also work on the same principle for understanding the intent of the content.

3.  The Actual Paraphrasing Procedure:

The third working phase of a paraphrasing tool is the stage where the stuff actually happens. It consists of two sub-steps that present the users with the paraphrased version of the original information.

1)   Paraphrase Identification (PI):

As the name depicts, this step is an identification stage and machine learning is responsible for carrying out this phase successfully.

The developers of paraphrasing tools train them with large and structured sets of sentence pairs to identify the flow of content and check if it makes any sense. So, the system (a paraphrasing tool) uses the knowledge learned from training to determine whether a phrase or sentence pair is its paraphrased version or not. For this purpose, the system (a paraphrasing tool) produces either ‘0’ or ‘1’ figures.

• 0: This figure indicates that sentence pairs have shifted from their original meaning and are not the paraphrased versions of each other.
• 1: This figure shows that the sentence pairs have the same meanings.

2)   Paraphrase Generation (PG):

As the name depicts, this step is responsible for generating the paraphrased version of the source text according to the learnings from previous phases.

Most paraphrasing tools work on different AI rephrasing modes. So, this step generates multiple paraphrased but fluent versions of the source text without changing the original meaning. However, machine learning works with several other strategies to preserve the original theme of the text and paraphrase the text.

Conclusion:

Paraphrasing is an excellent way of showing your understanding of a topic and showcasing your writing skills. However, the results of manual paraphrasing depend entirely on a writer’s skills. So, the manual process of paraphrasing is a challenging task for newbies. But thanks to AI, ML and NLP, that’s not the case anymore.

Artificial Intelligence and its sub-branches (ML and NLP) have automated the paraphrasing process. Now, you will just have to input the source text and choose the desired paraphrasing mode to generate new content from AI-based paraphrasing tools. So, technology has made paraphrasing easier.